alexgenovese/sdxl-custom-model:c29be0b9 – Run with an API on Replicate

Version

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alexgenovese /sdxl-custom-model:c29be0b9

Playground API

Input

Run this model in Node.js with one line of code:

npx create-replicate --model=alexgenovese/sdxl-custom-model

or set up a project from scratch

Install Replicate’s Node.js client library

npm install replicate

Set the REPLICATE_API_TOKEN environment variable

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run alexgenovese/sdxl-custom-model using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "alexgenovese/sdxl-custom-model:c29be0b9086f72d985151aef7f83ab5b79380e582287e787b09aa541ed7a0f48",
  {
    input: {
      seed: 12345,
      width: 1024,
      height: 1024,
      prompt: "",
      optimizer: 0.8,
      guidance_scale: 8,
      negative_prompt: "",
      num_inference_steps: 30
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library

pip install replicate

Set the REPLICATE_API_TOKEN environment variable

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client

import replicate

Run alexgenovese/sdxl-custom-model using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "alexgenovese/sdxl-custom-model:c29be0b9086f72d985151aef7f83ab5b79380e582287e787b09aa541ed7a0f48",
    input={
        "seed": 12345,
        "width": 1024,
        "height": 1024,
        "prompt": "",
        "optimizer": 0.8,
        "guidance_scale": 8,
        "negative_prompt": "",
        "num_inference_steps": 30
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run alexgenovese/sdxl-custom-model using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "c29be0b9086f72d985151aef7f83ab5b79380e582287e787b09aa541ed7a0f48",
    "input": {
      "seed": 12345,
      "width": 1024,
      "height": 1024,
      "prompt": "",
      "optimizer": 0.8,
      "guidance_scale": 8,
      "negative_prompt": "",
      "num_inference_steps": 30
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Install Cog

brew install cog

If you don’t have Homebrew, there are other installation options available.

Pull and run alexgenovese/sdxl-custom-model using Cog (this will download the full model and run it in your local environment):

cog predict r8.im/alexgenovese/sdxl-custom-model@sha256:c29be0b9086f72d985151aef7f83ab5b79380e582287e787b09aa541ed7a0f48 \
  -i 'seed=12345' \
  -i 'width=1024' \
  -i 'height=1024' \
  -i 'prompt=""' \
  -i 'optimizer=0.8' \
  -i 'guidance_scale=8' \
  -i 'negative_prompt=""' \
  -i 'num_inference_steps=30'

To learn more, take a look at the Cog documentation.

Pull and run alexgenovese/sdxl-custom-model using Docker (this will download the full model and run it in your local environment):

docker run -d -p 5000:5000 --gpus=all r8.im/alexgenovese/sdxl-custom-model@sha256:c29be0b9086f72d985151aef7f83ab5b79380e582287e787b09aa541ed7a0f48
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "seed": 12345,
      "width": 1024,
      "height": 1024,
      "prompt": "",
      "optimizer": 0.8,
      "guidance_scale": 8,
      "negative_prompt": "",
      "num_inference_steps": 30
    }
  }' \
  http://localhost:5000/predictions

Output

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